code: def test_dmpnn_model_reload():
      """Test DMPNNModel class for reloading the model"""
      torch.manual_seed(0)
  
      # load sample dataset
      current_dir = os.path.dirname(os.path.abspath(__file__))
      dataset_file = os.path.join(current_dir, "assets/qm9_mini.sdf")
      TASKS = ["alpha", "homo"]
      loader = SDFLoader(
          tasks=TASKS, featurizer=CoulombMatrix(29), sanitize=True
      )
      data = loader.create_dataset(dataset_file, shard_size=100)
  
      # initialize the model
      model_dir = tempfile.mkdtemp()
      model = DTNNModel(
          data.y.shape[1], model_dir=model_dir, batch_size=2
      )
  
      # fit the model
      model.fit(data, nb_epoch=10)
  
      # reload the model
      reloaded_model = DTNNModel(
          data.y.shape[1], model_dir=model_dir, batch_size=2
      )
      reloaded_model.restore()
  
      orignal_predict = model.predict(data)
      reloaded_predict = reloaded_model.predict(data)
      assert np.all(orignal_predict == reloaded_predict)
  
file_path: deepchem/deepchem/models/tests/test_dtnn.py
imports: import os
  import pytest
  import tempfile
  import numpy
  from deepchem.data import SDFLoader
  from deepchem.feat import CoulombMatrix
  from deepchem.utils import batch_coulomb_matrix_features
label_desc: Use image node_id 3 for calling a global function with example usage: test_dmpnn_model_reload() without return types